A New Thermodynamic Equilibrium-Based Metaheuristic

Broderick Crawford, Ricardo Soto, Enrique Cortés, Gino Astorga

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

In this work, a new optimization method inspired on the Thermodynamic Equilibrium is described to address nonlinear problems in continuous domains. In our proposal, each decision variable is treated as the most volatile chemical component of a saturated binary liquid mixture at a determined pressure and temperature. The optimization procedure is started with an initial solution randomly generated. The search is done by changing the equilibrium state of each mixture. The search is carried out by accepting worse solutions to avoid being left trapped in local optimums. The search includes the random change of the mixtures. The algorithm was tested by using known mathematical functions as benchmark functions showing competitive results in comparison with other metaheuristics.

Original languageEnglish
Title of host publicationCybernetics Approaches in Intelligent Systems - Computational Methods in Systems and Software 2017
EditorsRadek Silhavy, Petr Silhavy, Zdenka Prokopova
PublisherSpringer Verlag
Pages336-346
Number of pages11
ISBN (Print)9783319676173
DOIs
StatePublished - 2018
EventInternational Conference on Computational Methods in Systems and Software, CoMeSySo 2017 - Vsetin, Czech Republic
Duration: 12 Sep 201714 Sep 2017

Publication series

NameAdvances in Intelligent Systems and Computing
Volume661
ISSN (Print)2194-5357

Conference

ConferenceInternational Conference on Computational Methods in Systems and Software, CoMeSySo 2017
Country/TerritoryCzech Republic
CityVsetin
Period12/09/1714/09/17

Keywords

  • Combinatorial optimization
  • Metaheuristics
  • Single-solution based metaheuristic
  • Stochastic search methods

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